Report on the second Mock LISA Data Challenge

The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of several data sets containing simulated instrument noise and gravitational-wave sources of undisclosed parameters. Participants are asked...

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Bibliographic Details
Published in:arXiv.org 2007-11
Main Authors: Stanislav Babak, Baker, John G, Benacquista, Matthew J, Cornish, Neil J, Crowder, Jeff, Cutler, Curt, Larson, Shane L, Littenberg, Tyson B, Porter, Edward K, Vallisneri, Michele, Vecchio, Alberto, Auger, Gerard, Barack, Leor, Blaut, Arkadiusz, Bloomer, Ed, Brown, Duncan A, Christensen, Nelson, Clark, James, Fairhurst, Stephen, Gair, Jonathan R, Halloin, Hubert, Hendry, Martin, Jimenez, Arturo, Krolak, Andrzej, Mandel, Ilya, Messenger, Chris, Meyer, Renate, Mohanty, Soumya, Nayak, Rajesh, Petiteau, Antoine, Pitkin, Matt, Plagnol, Eric, Prix, Reinhard, Robinson, Emma L, Roever, Christian, Pavlin Savov, Stroeer, Alexander, Toher, Jennifer, Veitch, John, Vinet, Jean-Yves, Wen, Linqing, Whelan, John T, Woan, Graham
Format: Article
Language:English
Subjects:
Data analysis
Data processing
Datasets
Gravitational waves
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Summary:The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of several data sets containing simulated instrument noise and gravitational-wave sources of undisclosed parameters. Participants are asked to analyze the data sets and report the maximum information about source parameters. The challenges are being released in rounds of increasing complexity and realism: in this proceeding we present the results of Challenge 2, issued in January 2007, which successfully demonstrated the recovery of signals from supermassive black-hole binaries, from ~20,000 overlapping Galactic white-dwarf binaries, and from the extreme-mass-ratio inspirals of compact objects into central galactic black holes.
ISSN:2331-8422
DOI:10.48550/arxiv.0711.2667